Core Features

Zynthetix offers a range of core features designed to facilitate the generation of high-quality synthetic data. Below are the detailed descriptions of the core features available on the platform.

Data Input Methods

Zynthetix supports multiple data input methods to accommodate different user needs:

• Text Prompt: Users can provide a text prompt which will be analyzed and categorized to generate synthetic text data.
• CSV File: Users can upload a CSV file containing existing data, which will be augmented with additional synthetic rows.
• ZIP File: Users can upload a ZIP file containing images, which will be used to generate high-quality synthetic images.

Data Analysis and Categorization

Using advanced machine learning models like RoBERTa, Zynthetix can analyze and categorize input data to identify column names and data categories. This ensures that the generated synthetic data is accurate and relevant.

Synthetic Data Generation

Zynthetix leverages state-of-the-art models to generate synthetic data:

• GPT-NeoX: Utilized for generating synthetic text data based on the identified column names and data categories.
• StyleGAN3: Used for generating high-quality synthetic image data from the uploaded ZIP files.

Data Filtering and Finalization

Users can review and filter the generated synthetic data through a user-friendly interface. This allows users to make adjustments and finalize the data before downloading it.

Model Training and Evaluation (Optional)

Zynthetix provides options for users to upload pre-trained models for further training with synthetic data. The platform offers tools to evaluate model performance, showing improvements in accuracy and other relevant metrics.

Privacy-Preserving Data Modification

To ensure sensitive information is protected, Zynthetix includes privacy-preserving techniques for modifying the dataset. This helps in maintaining data privacy while using synthetic data for model training.

Monitoring and Maintenance

Zynthetix integrates with monitoring tools like Prometheus and Grafana to provide continuous monitoring and maintenance of deployed models. This ensures smooth operation and performance tracking.

Scalability

The platform is designed to scale with the needs of users, handling both small projects and large-scale applications efficiently. Zynthetix utilizes cloud infrastructure to provide scalable synthetic data generation solutions.

Integration with Cloud Services

Zynthetix integrates seamlessly with various cloud services, including AWS EC2, S3, and SageMaker, to provide a robust infrastructure for data storage, model deployment, and managed training.

User Authentication

Secure user authentication is ensured through the integration of Clerk, providing a secure and seamless login experience for users.

Deployment Options

Zynthetix offers flexible deployment options, including cloud services and on-premise deployment, catering to different user requirements.

These core features make Zynthetix a comprehensive and powerful platform for synthetic data generation, addressing the needs of businesses, researchers, and developers.